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A marketing team wants to analyze social media sentiment in near real-time. They will use Azure Event Hubs to capture tweets and need to aggregate sentiment scores over 5-minute windows. The aggregated results must be stored in Azure Blob Storage for later analysis. Which Azure service should they use to perform the stream processing?

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A marketing team wants to analyze social media sentiment in near real-time. They will use Azure Event Hubs to capture tweets and need to aggregate sentiment scores over 5-minute windows. The aggregated results must be stored in Azure Blob Storage for later analysis. Which Azure service should they use to perform the stream processing?

Answer choices

Why each option matters

Good practice is not just finding the correct option. The wrong answers often show the exact trap the exam wants you to fall into.

A

Best answer

Azure Stream Analytics

Azure Stream Analytics is specifically designed for real-time stream processing and can easily ingest from Event Hubs, apply windowed aggregations, and output to Blob Storage.

B

Distractor review

Azure Data Factory

Azure Data Factory is an orchestration and data integration service for batch processing, not real-time stream processing.

C

Distractor review

Azure Databricks

Azure Databricks can handle stream processing via Structured Streaming, but it requires more configuration and is overkill for a simple aggregation task best suited for Stream Analytics.

D

Distractor review

Azure Synapse Analytics

Azure Synapse Analytics is an analytics service for querying and processing data at scale, but it is not designed for real-time stream processing from Event Hubs directly.

Common exam trap

Common exam trap: answer the scenario, not the keyword

Many certification questions include familiar terms but test a specific constraint. Read the exact wording before choosing an answer that is generally true but wrong for this case.

Technical deep dive

How to think about this question

This question should be treated as a scenario, not a definition check. Identify the problem, the constraint and the best action. Then compare each option against those facts.

KKey Concepts to Remember

  • Read the scenario before looking for a memorised answer.
  • Find the constraint that changes the correct option.
  • Eliminate answers that are true in general but not in this case.
  • Use explanations to understand the rule behind the answer.

TExam Day Tips

  • Underline the problem statement mentally.
  • Watch for words such as best, first, most likely and least administrative effort.
  • Review why wrong options are wrong, not only why the correct option is correct.

Related practice questions

Related DP-900 practice-question pages

Use these pages to review the topic behind this question. This is how one missed question becomes focused revision.

More questions from this exam

Keep practising from the same exam bank, or move into a focused topic page if this question exposed a weak area.

Question 1

A data engineer needs to process streaming data from IoT devices and store the results in Azure Data Lake Storage for long-term analytics. The data must be processed in near real-time to detect anomalies and trigger alerts. Which Azure service should the engineer use for stream processing?

Question 2

A data engineer needs to query data stored in CSV files in Azure Data Lake Storage Gen2 using T-SQL in Azure Synapse Analytics, without loading the data into the database. Which feature should they use?

Question 3

A data engineer needs to process raw clickstream data from multiple websites that is stored in Azure Blob Storage as JSON files. The processing must run automatically every hour, transform the data into a structured format for reporting, and handle schema changes in the source data without manual intervention. Which Azure service should be used?

Question 4

A data engineer is designing a data lake architecture in Azure. They plan to first ingest raw data from various sources into a landing zone in Azure Data Lake Storage Gen2. Then they will clean, validate, and deduplicate that data in a second zone. Finally, they will create aggregated, business-ready datasets in a third zone for analysts. This layered approach is known as which architecture?

Question 5

A data engineer needs to transform large datasets stored in Azure Data Lake Storage Gen2 using Python and Apache Spark. They want a serverless compute option that automatically scales and requires no cluster management. Which Azure service should they use?

Question 6

A company collects customer feedback forms. Each form contains always-present fields like CustomerID and SubmissionDate, but also a free-text Comments field and optional fields like Rating or ProductCategory that vary between forms. How should this data be classified?

FAQ

Questions learners often ask

What does this DP-900 question test?

Read the scenario before looking for a memorised answer.

What is the correct answer to this question?

The correct answer is: Azure Stream Analytics — Azure Stream Analytics is a serverless, real-time analytics service designed for processing streaming data. It can ingest data from Azure Event Hubs, apply windowed aggregations (e.g., 5-minute tumbling windows), and output results to Azure Blob Storage, Power BI, or other sinks. Other services like Azure Data Factory are for batch orchestration, Azure Databricks is more general-purpose and requires more setup for simple stream processing, and Azure Synapse Analytics is primarily for analytical workloads on static data, not real-time streaming ingestion.

What should I do if I get this DP-900 question wrong?

Then try more questions from the same exam bank and focus on understanding why the wrong options are tempting.

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